2016
DOI: 10.48550/arxiv.1610.02689
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The Impact of Modeling Errors on Interferometer Calibration for 21 cm Power Spectra

Aaron Ewall-Wice,
Joshua S. Dillon,
Adrian Liu
et al.
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Cited by 3 publications
(4 citation statements)
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“…If we take as a worst-case, the foreground precision requirement to be 10,000:1, then our target precision is 0.01%, while our current best demonstrated absolute accuracy is ∼1% but gets to 100% in the sidelobes. An error propagation study by Ewall-Wice et al (2016b) suggests that a flat 1% (0.04 dB) precision of the HERA beam provides sufficient suppression of foreground residuals to enable detection of most power spectrum modes outside the wedge. In a similar study, Shaw et al (2015) have set a requirement to know the CHIME to beamwidth to 0.1%, which for a Gaussian beam translates to ∼1dB error bars at a −40dB level.…”
Section: Overall Performancementioning
confidence: 99%
See 1 more Smart Citation
“…If we take as a worst-case, the foreground precision requirement to be 10,000:1, then our target precision is 0.01%, while our current best demonstrated absolute accuracy is ∼1% but gets to 100% in the sidelobes. An error propagation study by Ewall-Wice et al (2016b) suggests that a flat 1% (0.04 dB) precision of the HERA beam provides sufficient suppression of foreground residuals to enable detection of most power spectrum modes outside the wedge. In a similar study, Shaw et al (2015) have set a requirement to know the CHIME to beamwidth to 0.1%, which for a Gaussian beam translates to ∼1dB error bars at a −40dB level.…”
Section: Overall Performancementioning
confidence: 99%
“…A similar error propagation study suggests that an accuracy of 1% across the beam will substantially reduce foreground bias for HERA and that other telescopes like SKA might require even better side-lobe beam accuracy (Ewall-Wice et al 2016b). Interpreting these requirements into a requirement on systematic error in the beam map, we assume that the multiplicative errors will, as is common for gain errors, have log-normal distribution.…”
Section: Introductionmentioning
confidence: 99%
“…In addition to ba-sic signal-to-noise requirements demanding thousands of hours of observing time, the experiments must deal with the so-called "foregrounds" (which are essentially all other sources of radio emission) that can potentially eliminate a power spectrum detection or bias a measurement. Strategies to understand and correct for the effects of foregrounds, including how foregrounds interact with the instrument response, are the subject of many investigations (Morales et al 2006;Jelić et al 2008Jelić et al , 2010Bernardi et al 2009;Chapman et al 2012;Trott et al 2012;Morales et al 2012;Vedantham et al 2012;Thyagarajan et al 2015;Ewall-Wice et al 2016;Barry et al 2016;Trott & Wayth 2016;Patil et al 2016). Nevertheless, the bright foreground sources (such as diffuse Galactic radio emission and extragalactic radio galaxies and quasars) are spectrally smooth (Di Matteo et al 2002;Dillon et al 2014;Parsons et al 2014;Zaldarriaga et al 2004;Offringa et al 2016) which, in principle, confines the signal from these sources to the lowest-order (slowest varying) terms in the 1/frequency dimension of a power spectrum.…”
Section: Introductionmentioning
confidence: 99%
“…Work by Barry et al (2016) to simulate the effects of antenna cable reflections in the MWA signal chain demonstrated the requirement for smoothness across the bandpass. More recently, Offringa et al (2016) and Ewall-Wice et al (2016) studied the impact of calibration errors due to unmodelled foreground sources, and found that residual source chromatic structure impedes the ability of instruments to perform EoR science. Relevant to this work, Trott & Wayth (2016) used an ideal estimator to quantify the tolerances on smoothness of the intrinsic SKA-Low bandpass response required for the proposed EoR/CD experiments to be undertaken successfully.…”
Section: Introductionmentioning
confidence: 99%